Real-Time Point Clouds Zed Mini

Real-Time Point Clouds with the Zed Mini

Lately, I have been experimenting with real-time point clouds with the Zed Mini from Stereolabs. Firstly, I am a big believer in real-time point clouds being a viable solution for co-located, virtual reality experiences. Concurrently, I am also interested in examining the development of this technology, and how we use artificial intelligence and machine learning to examine the world we live in. The Zed Mini functions much in the same way that the Kinect Azure does. The big difference is that the Kinect is more plug and play, while the Zed needs external libraries. Lastly, another big difference is the image and point-cloud quality, with the Zed being far superior. For some people, the fact that some of the tools need to be built using CMake and Visual Studio will be a deal-breaker. Stereolab provides resources in their Git Repository.

The Zed Tools

After I built the tools from the source, I now have access to some tools in samples/bin. As an example, the most immediately useful is ZED_SVO_Recording.exe. Firstly, this allows me to write an SVO file to disk. SVO is a proprietary format from Stereolab. Most importantly, this format allows for the recording of all the data from the Zed camera into a compressed file format. This will allow me to construct the point-clouds after shooting. In order to run these tools, I need to call them from the command-line. For ZED_SVO_Recording the only argument I need is a path to where I want the SVO file saved. So assuming I am in the shell in the correct directory, you would just write:

ZED_SVO_Recording.exe c:SVO_save_folder/mySVOFile.svo

The prompt should start scrolling frame numbers, and a ctrl-c will break the operation. One the SVO is saved, one can use some of the other tools that Stereolab provides.

Zed in Touchdesigner

I am working with a friend, Shaoyu Su to get TensorFlow and YOLO working through the Zed and Touchdesigner for object recognition and tracking.

You can download a free version of Touchdesigner here:

Other Houdini Tutorials:

Lidar with Ouster and Touchdesigner

Real-Time Lidar with Touchdesigner and Ouster

I have been wanting to experiment with real-time lidar using the newer, small Ouster Units and Touchdesigner. The last time I did any experiments with real-time lidar it was with a Velodyne 16. Using Touchdesigner we can now easily use lidar that runs in real-time. Ever since I first got to play with that Velodyne 16, I have been an advocate of the point cloud as a means of geometry display. Points are light in memory and can contain their RGB information. Because of this, it is far easier to display real-time evolving data than it would be to try to mesh, UV and texture. Even as a post-process the very concept of meshing will always be subject to artificating and resolution problems.

Lidar Compared Depth Based Techniques

Currently, real-time Lidar solutions lag behind any depth-based solution like a Kinect Azure or a Zed Camera in regards to a resolution. As well, we do not yet get any RGB data. Moreover, to get RGB data we would need an additional device, such as a small Virtual Reality camera. However, we do get an intensity value. This acts like a black and white image.

Testing

One of my students was able to get a loaned out OS2, a $16,000 unit so that he can use it in his Masters Thesis at USC School of Cinematic Arts. We used the Lidar with the Ouster running through Touchdesigner. Touchdesigner has an Ouster Top and Chop that allows us to pull in all the data. The unit has the following specs:

  • The OS0 lidar sensor: an ultra-wide field of view sensor with 128 lines of resolution
  • Two new 32 channel sensors: both an OS0 and OS2 version
  • New beam configuration options on 32 and 64 beam sensors

Volumetric Video

You can see some of my research with Google and the Foundry here. I believe this is how we will eventually represent large, realistic datasets for both virtual and augmented reality. Self-driving car and machine learning have brought us smaller, better and faster lidar and I am seeing the technology trickle down into interesting alternative use cases.

Intensity Pass

These images below show the full image range of a normalized “intensity” pass.

Other Houdini Tutorials:

Instancing Geometry with Touchdesigner

Instancing with Touchdesigner

In an introduction to instancing geometry in Touchdesigner, I show how we can instance geometry on the GPU.  Instancing allows us to create multiple copies of an object. Since they are just copies, we can create a large number of copies. Moreover, we can give them random scale, coloring, and rotation for variety. In Touchdesigner we use  CHOPS, and now TOPS in order to provide channels for instance. As a result, we can alter and change the instances over time.
An introduction to instancing geometry in Touchdesigner will provide a basic understanding of:

  • How we can generate channel data for Instancing in CHOPS
  • How we use that data on a Geometry Container

You can download a free version of Touchdesigner here.

Other Houdini Tutorials: